Under the background of global warming, the frequent occurrence and long-term persistence of drought events have substantial negative effects on agricultural production. As the main maize production area in midwestern Jilin Province, frequent drought and a shortage of irrigation water pose substantial threats to the production of maize. We analyzed the balance of water supply and demand in each growth period and the degree of maize yield affected by drought. The results indicate that the FIO-ESM climate model can effectively simulate the changes in temperature and precipitation, and was highly applicable to the study area. From 1980 to 2020, the drought risk indices for the sowing to jointing, jointing to tasseling, tasseling to milk-ripe, and milk-ripe to maturity stages were 0.62, 0.52, 0.48, and 0.60, respectively. In the future, the chances of a RCP8.5 scenario drought risk and an enhanced RCP4.5 scenario have eased. Spatially, the high-risk areas shift in a “west−central−southwest” pattern. Effective precipitation will decrease in the future, while the increasing water requirement of maize increases the dependence on irrigation water. The irrigation requirement index is more than 70% for all periods, particularly in the milk-ripe to maturity stage. The relative meteorological yields were positively correlated with the CWDI of the whole growth period, with the rate of reduction in maize yield and the yield reduction coefficient of variation at a high level of risk between 1980 and 2020. In the future, the negative impact of drought risk on the yield of maize lessened with no obvious trend in production. In particular, the rate of reduction and reduction coefficient of variation for the RCP8.5 scenario were 1.24 and 1.09, respectively.

As a key spatial platform for implementing China’s Northeast Revitalization Strategy, coordinated development of production–living–ecological (PLE) functions in the Changchun Metropolitan Area is crucial for high-quality regional development. This study uses 24 counties (districts) in the metropolitan area as analytical units and develops a quantitative indicator system to evaluate PLE functions. We integrate the entropy-weighted TOPSIS method, social network analysis (SNA), and geographically and temporally weighted regression (GTWR) to examine the spatiotemporal dynamics, spatial correlation networks, and driving mechanisms of the three functions from 2013 to 2023. Temporally, the production function follows a growth–decline–recovery trajectory, the living function increases overall despite fluctuations, and the ecological function strengthens continuously. Overall, the three functions increasingly exhibit coupling and synergy. Spatially, the production function concentrates in core areas and diffuses along major axes. The living function is led by the core and followed by county-level catch-up. The ecological function is higher in the east, relatively stable in the west, and connected by corridors, together forming a multi-center, axis-based synergistic pattern. In the spatial correlation networks, densities of the production and ecological networks remain largely stable, whereas the living network becomes markedly denser. The three networks display distinct topologies and continue to evolve structurally. For driving mechanisms, the GTWR model provides the best fit. Geographic proximity positively contributes to the formation of all three functional networks, while the eight explanatory factors show pronounced spatiotemporal heterogeneity. These findings provide an evidence base for optimizing functional coordination and implementing differentiated spatial governance in metropolitan areas.

Against the background of ecological civilization construction and the transformation of state-owned forest regions after the logging ban, balancing economic development with ecological protection has become an important issue in China’s forest areas. The development of the non-timber forest-based economy plays a critical role in advancing high-quality, green economic growth in China and contributes significantly to sustainable resource utilization. This study examines data from key state-owned forests and the natural environment in the Changbai Mountain region of Jilin Province from 2013 to 2023. A comprehensive evaluation model and a coupling coordination model, based on the human–land relationship framework, are employed to assess temporal changes in economic growth quality, ecological environment carrying capacity, and their coupling coordination. The quality of non-timber forest-based economic growth exhibited an overall upward trend. Fusong County, Wangqing County, and Dunhua City consistently maintained high levels, while Helong City experienced the largest decline. The spatial distribution followed a “high center, low periphery” pattern, with the 2015 logging ban serving as a key turning point in promoting ecological transformation. The per capita ecological environment carrying capacity improved across the region, with significant increases in Dunhua, Helong, and Antu Counties. A radial decline from the central to peripheral areas was observed, with the highest values in Wangqing and Antu Counties. The coupling coordination degree between economic growth and ecological environment fluctuated between 0.4 and 0.6. In 2023, Wangqing County reached a state of intermediate coordination (index > 0.7), whereas Linjiang remained in a dysfunctional state (index < 0.5). Spatial clustering of coordination weakened over time, as indicated by Moran’s I values of 0.32, 0.21, and 0.09 in 2013, 2018, and 2023, respectively. These findings provide a quantitative foundation for promoting the coordinated development of human–land systems and guiding high-quality regional growth in forest-based economic zones.